Perbandingan performa Algoritma Neural Network, Regresi Linier, dan Random Forest dalam simulasi prediksi angka kematian pasien COVID-19 di Indonesia

Muhammad Reza Redo I, Artia Irianti

Abstract


Seluruh dunia saat ini sedang menghadapi situasi pandemi penyakit menular Corona 2019, yang juga disebut "COVID-19". Hingga akhir Juni 2021, pandemi COVID-19 terus meningkat di Indonesia, jumlah orang yang terkena dampak Covid-19 terus bertambah. Makalah ini dirancang untuk memodelkan algoritma dan mengetahui algoritma apa yang paling cocok/mendekati nilai aslinya dalam memprediksi angka kematian berdasarkan dataset WHO dan dataset Johns Hopkins University Center for Systems Science and Engineering. Dalam penulisan ini, algoritma yang akan di modelkan untuk melakukan prediksi adalah Algoritma Neural Network, Regresi Linier, dan Random Forest. Hasil dari pemodelan tersebut akan di visualisasikan sehingga performa dari ke-tiga algoritma tersebut dapat diukur.


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